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The paper shows some of benefits of multi-unitary decomposition in signal analysis applications. It is emphasized that decompositions of complex discrete-time signals onto a single basis provide an incomplete and in such way potentially misleading image of the signals in signal analysis applications. It is shown that the multi-unitary decimated filter banks which decompose the analyzed signal onto several bases of the given vector space can serve as a tool which provides a more complete information about the signal and at the same time the filter banks can enjoy efficient polyphase component implementation of maximally decimated, i. e. nonredundant, filter banks. An insight into the multi-unitary signal decomposition is provided. It is shown that the multiple-bases representation leads to an efficient computation of frequency domain representations of signals on a dense not necessarily uniform frequency grid. It is also shown that the multiple-bases representation can be useful in the detection of tones in digital implementations of multifrequency signaling, and in receivers of chirp systems. A proof is provided that there are possible benefits of the multiple-bases representations in de-noising applications.

- Publication
- IEICE TRANSACTIONS on Fundamentals Vol.E83-A No.1 pp.109-120

- Publication Date
- 2000/01/25

- Publicized

- Online ISSN

- DOI

- Type of Manuscript
- PAPER

- Category
- Digital Signal Processing

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Pavol ZAVARSKY, Takeshi MYOKEN, Noriyoshi KAMBAYASHI, Shinji FUKUMA, Masahiro IWAHASHI, "A Multi-Unitary Decomposition of Discrete-Time Signals in Signal Analysis" in IEICE TRANSACTIONS on Fundamentals,
vol. E83-A, no. 1, pp. 109-120, January 2000, doi: .

Abstract: The paper shows some of benefits of multi-unitary decomposition in signal analysis applications. It is emphasized that decompositions of complex discrete-time signals onto a single basis provide an incomplete and in such way potentially misleading image of the signals in signal analysis applications. It is shown that the multi-unitary decimated filter banks which decompose the analyzed signal onto several bases of the given vector space can serve as a tool which provides a more complete information about the signal and at the same time the filter banks can enjoy efficient polyphase component implementation of maximally decimated, i. e. nonredundant, filter banks. An insight into the multi-unitary signal decomposition is provided. It is shown that the multiple-bases representation leads to an efficient computation of frequency domain representations of signals on a dense not necessarily uniform frequency grid. It is also shown that the multiple-bases representation can be useful in the detection of tones in digital implementations of multifrequency signaling, and in receivers of chirp systems. A proof is provided that there are possible benefits of the multiple-bases representations in de-noising applications.

URL: https://global.ieice.org/en_transactions/fundamentals/10.1587/e83-a_1_109/_p

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@ARTICLE{e83-a_1_109,

author={Pavol ZAVARSKY, Takeshi MYOKEN, Noriyoshi KAMBAYASHI, Shinji FUKUMA, Masahiro IWAHASHI, },

journal={IEICE TRANSACTIONS on Fundamentals},

title={A Multi-Unitary Decomposition of Discrete-Time Signals in Signal Analysis},

year={2000},

volume={E83-A},

number={1},

pages={109-120},

abstract={The paper shows some of benefits of multi-unitary decomposition in signal analysis applications. It is emphasized that decompositions of complex discrete-time signals onto a single basis provide an incomplete and in such way potentially misleading image of the signals in signal analysis applications. It is shown that the multi-unitary decimated filter banks which decompose the analyzed signal onto several bases of the given vector space can serve as a tool which provides a more complete information about the signal and at the same time the filter banks can enjoy efficient polyphase component implementation of maximally decimated, i. e. nonredundant, filter banks. An insight into the multi-unitary signal decomposition is provided. It is shown that the multiple-bases representation leads to an efficient computation of frequency domain representations of signals on a dense not necessarily uniform frequency grid. It is also shown that the multiple-bases representation can be useful in the detection of tones in digital implementations of multifrequency signaling, and in receivers of chirp systems. A proof is provided that there are possible benefits of the multiple-bases representations in de-noising applications.},

keywords={},

doi={},

ISSN={},

month={January},}

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TY - JOUR

TI - A Multi-Unitary Decomposition of Discrete-Time Signals in Signal Analysis

T2 - IEICE TRANSACTIONS on Fundamentals

SP - 109

EP - 120

AU - Pavol ZAVARSKY

AU - Takeshi MYOKEN

AU - Noriyoshi KAMBAYASHI

AU - Shinji FUKUMA

AU - Masahiro IWAHASHI

PY - 2000

DO -

JO - IEICE TRANSACTIONS on Fundamentals

SN -

VL - E83-A

IS - 1

JA - IEICE TRANSACTIONS on Fundamentals

Y1 - January 2000

AB - The paper shows some of benefits of multi-unitary decomposition in signal analysis applications. It is emphasized that decompositions of complex discrete-time signals onto a single basis provide an incomplete and in such way potentially misleading image of the signals in signal analysis applications. It is shown that the multi-unitary decimated filter banks which decompose the analyzed signal onto several bases of the given vector space can serve as a tool which provides a more complete information about the signal and at the same time the filter banks can enjoy efficient polyphase component implementation of maximally decimated, i. e. nonredundant, filter banks. An insight into the multi-unitary signal decomposition is provided. It is shown that the multiple-bases representation leads to an efficient computation of frequency domain representations of signals on a dense not necessarily uniform frequency grid. It is also shown that the multiple-bases representation can be useful in the detection of tones in digital implementations of multifrequency signaling, and in receivers of chirp systems. A proof is provided that there are possible benefits of the multiple-bases representations in de-noising applications.

ER -